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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 20 of 178  /  [Next]  
Committee Date Time Place Paper Title / Authors Abstract Paper #
CQ, ICM, NS, NV
(Joint)
2021-11-25
11:05
Fukuoka JR Hakata Stn. Hakata EkiHigashi Rental Room
(Primary: On-site, Secondary: Online)
[Encouragement Talk] Overhead Reduction for High-Quality Graph-Based Point Cloud Delivery
Soushi Ueno, Takuya Fujihashi (Osaka Univ.), Toshiaki Koike-Akino (MERL), Takashi Watanabe (Osaka Univ.) NS2021-85
The point cloud expresses three-dimensional (3D) information by using many points on 3D space. It is important to be abl... [more] NS2021-85
pp.7-12
CAS, NLP 2021-10-14
10:25
Online Online Performance Evaluation of All-Pass Fractional Delay Digital Filters under Coefficient Quantization
Shunsuke Koshita (Hachinohe Inst. of Tech.) CAS2021-18 NLP2021-16
In this paper, performance of IIR fractional delay digital filters given by all-pass transfer functions is evaluated in ... [more] CAS2021-18 NLP2021-16
pp.7-11
BioX, ISEC, SITE, ICSS, EMM, HWS, IPSJ-CSEC, IPSJ-SPT [detail] 2021-07-19
16:55
Online Online Evaluation on Biometric Template Protection System Based on Somewhat Homomorphic Encryption
Hiroto Tamiya, Toshiyuki Isshiki, Kengo Mori (NEC), Satoshi Obana (Hosei Univ.), Tetsushi Ohki (Shizuoka Univ.) ISEC2021-21 SITE2021-15 BioX2021-22 HWS2021-21 ICSS2021-26 EMM2021-26
Many biometric template protection systems have been proposed to perform biometric authentication while keeping the biom... [more] ISEC2021-21 SITE2021-15 BioX2021-22 HWS2021-21 ICSS2021-26 EMM2021-26
pp.68-73
PN, NS, OCS
(Joint)
2021-06-25
10:45
Online Online Overhead Reduction for Point Cloud Wireless Delivery using Graph Signal Processing
Soushi Ueno, Takuya Fujihashi (Osaka Univ.), Toshiaki Koike-Akino (MERL), Takashi Watanabe (Osaka Univ.) NS2021-29
Graph-based compression can compact the signal energy of three-dimensional (3D) point cloud and realize high quality 3D ... [more] NS2021-29
pp.21-26
RCS 2021-06-25
10:20
Online Online A Study on Deep Unfolding-Aided Quantized AMP for High-Dimensional Signal Detection
Atsunori Shimamura, Takumi Takahashi (Osaka Univ), Shinsuke Ibi (Doshisha Univ), Seiichi Sampei (Osaka Univ) RCS2021-68
We consider a look-up table (LUT)-based multi-user detection (MUD) via quantized approximate message passing (AMP) in la... [more] RCS2021-68
pp.226-231
NLP, CCS 2021-06-11
11:50
Online Online A Study on Image Compression Method based on Color Quantization Method by Sigma-Delta Cellular Neural Network
Fumitoshi Nakashima, Yuka Ito, Ai Mizuno (Chukyo Univ.), Ryohei Mizutani (YAMAZAKI MAZAK), Misa Fujita (Chukyo Univ.), Tsuyoshi Otake (Tamagawa Univ), Hisashi Aomori (Chukyo Univ.) NLP2021-5 CCS2021-5
In recent years, Web services have become common and their use has been widespread.
The PNG image format is basically u... [more]
NLP2021-5 CCS2021-5
pp.20-23
QIT
(2nd)
2021-05-25
09:30
Online Online Acceleration of Extreme Learning Machines by Dequantization of Quantum Singular Value Decomposition
Iori Takeda, Souichi Takahira, Kousuke Mitarai, Keisuke Fujii (Osaka Univ.)
In 2016, the quantum recommendation system was proposed by Kerenidis and Prakash, and it was shown that the singular val... [more]
EMM, IT 2021-05-21
13:35
Online Online A Study on Feature Extraction Suitable for Double JPEG Compression Analysis Based on Statistical Bias Observation of DCT Coefficients
Daichi Takeshita, Minoru Kuribayashi, Nobuo Funabiki (Okayama Univ.) IT2021-12 EMM2021-12
Pictures taken by smart phones and camera devices are generally compressed by JPEG by default when they are saved. If su... [more] IT2021-12 EMM2021-12
pp.66-71
NLP, MSS
(Joint)
2021-03-16
10:45
Online Online Approximate formula of the mean square quantization error of golden ratio encoders
Yoshikatsu Kashiwabara, Yutaka Jitsumatsu (Kyushu Univ.) NLP2020-63
The Golden Ratio Encoder (GRE) is a type of analog-to-digital (A/D) conversion method. GRE expands the input analog valu... [more] NLP2020-63
pp.47-52
HWS, VLD [detail] 2021-03-03
11:15
Online Online The Design and Development of of Quantized Neural Networks Library for Exact Hardware Emulation
Masato Kiyama, Yasuhiro Nakahara, Motoki Amagasaki, Masahiro Iida (Kumamoto Univ.) VLD2020-70 HWS2020-45
Quantization is used to speed up execution time and save power when runnning Deep neural networks (DNNs) on edge devices... [more] VLD2020-70 HWS2020-45
pp.18-23
SIP, IT, RCS 2021-01-21
11:45
Online Online A Study on Secret Key Agreement Scheme by Vector Quantization of Correlated MIMO Channel Matrix
Tomoyuki Higashide, Shinsuke Ibi (Doushisha Univ.), Takumi Takahashi (Osaka Univ.), Hisato Iwai (Doushisha Univ.) IT2020-69 SIP2020-47 RCS2020-160
In the wireless communication, secret key agreement schemes on physical layer attracts attentions for protecting communi... [more] IT2020-69 SIP2020-47 RCS2020-160
pp.34-39
EA, ASJ-H, EMM 2020-11-20
09:00
Online Online [Poster Presentation] Evaluation on JPEG Image Compression History Analysis Using Histogram of DCT Coefficients with Different Block Size
Naoya Nakajima, Minoru Kuribayashi, Nobuo Funabiki (Okayama Univ.) EA2020-30 EMM2020-45
The image taken with a digital comera is usually JPEG-compressed when saved. On the other hand, the tampered image is ca... [more] EA2020-30 EMM2020-45
pp.48-53
MBE, NC, NLP, CAS
(Joint) [detail]
2020-10-29
16:10
Online Online Numerical research on effects of quantization in SNN learned by backpropagation
Yumi Watanabe, Jun Ohkubo (Saitama Univ.) NC2020-14
There are many studies to quantize the parameters of neural networks. For example, while there are methods of quantizing... [more] NC2020-14
pp.29-33
EA, ASJ-H 2020-08-07
14:55
Online Online Effect of Spatial Auditory Masking on Perception of Quantization Noise
Yuma Yamanaka (Grad. Sch. of Akita Pref. Univ.), Masayuki Nishiguchi, Kanji Watanabe, Shouichi Takane, Koji Abe (Akita Pref. Univ.) EA2020-18
Audio reproduction systems, such as 22.2 multi-channel system, generating sound source directions by synthesizing three ... [more] EA2020-18
pp.29-34
SIS 2020-03-05
13:30
Saitama Saitama Hall
(Cancelled but technical report was issued)
A Proposal of Color Quantization Algorithm Based on Weighted Principle Component Analysis Using Saturation
Seiichi Kojima, Tomoki Kusunoki (Yamaguchi Univ.), Yoshiaki Ueda (Fukuoka Univ.), Noriaki Suetake, Eiji Uchino (Yamaguchi Univ.) SIS2019-40
In a 24 bit full color image, there are about 16 millions possible colors. On the other hand, in a limited color image, ... [more] SIS2019-40
pp.19-22
ITE-HI, IE, ITS, ITE-MMS, ITE-ME, ITE-AIT [detail] 2020-02-27
14:40
Hokkaido Hokkaido Univ.
(Cancelled but technical report was issued)
A Note on Eye Gaze Based User-specific Interest Estimation for Images -- Estimation Performance Improvement Based on sMVCCA including Ordinal Label Dequantization --
Masanao Matsumoto (Hokkaido Univ.), Naoki Saito (NIT, Kushiro College), Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.)
This paper presents supervised multiview canonical correlation analysis via ordinal label dequantization (sMVCCA-OLD) fo... [more]
SAT, SANE
(Joint)
2020-02-19
10:00
Okinawa   Multi-bit Δ-Σ Modulator Based DSP Transceiver for High Dynamic Range Chirp Radar System
Tomoki Abe, Yamao Yasushi (UEC) SANE2019-97
This paper proposes a novel digital signal processing (DSP) radar transceiver that consists of a multi-bit quadrature Δ-... [more] SANE2019-97
pp.1-6
SDM 2020-01-28
14:45
Tokyo Kikai-Shinko-Kaikan Bldg. [Invited Talk] Can in-memory/Analog Accelerators be a Silver Bullet for Energy-efficient Inference?
Jun Deguchi, Daisuke Miyashita, Asuka Maki, Shinichi Sasaki, Kengo Nakata, Fumihiko Tachibana, Ryuichi Fujimoto (KIOXIA) SDM2019-85
This presentation introduces and discuss recent trends on in-memory/analog computing for deep learning inference, which ... [more] SDM2019-85
p.11
NLP, NC
(Joint)
2020-01-24
13:50
Okinawa Miyakojima Marine Terminal Ternarized Backpropagation for Edge AI and its FPGA Implementation
Tatsuya Kaneko, Yoshiharu Yamagishi, Hiroshi Momose, Tetsuya Asai (Hokkaido Univ.) NLP2019-95
In recent years there has been growing more interest in machine/deep learning.
As following this movement, many types ... [more]
NLP2019-95
pp.53-58
IT, SIP, RCS 2020-01-23
16:15
Hiroshima Hiroshima City Youth Center [Invited Talk] Design of Δ∑ modulators matched to their connected systems
Shuichi Ohno (Hiroshima Univ.) IT2019-58 SIP2019-71 RCS2019-288
Quantization maps a large set of input values onto a smaller set of output values, which is fundamental for digital proc... [more] IT2019-58 SIP2019-71 RCS2019-288
p.131
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